{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T09:21:59Z","timestamp":1649150519997},"reference-count":28,"publisher":"Hindawi Limited","license":[{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"funder":[{"DOI":"10.13039\/501100012226","name":"National Key Technology Support Program","doi-asserted-by":"crossref","award":["2012AA02A606","2013QNA5018"],"award-info":[{"award-number":["2012AA02A606","2013QNA5018"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2014]]},"abstract":"<jats:p>Gastroscopic examination is one of the most common methods for gastric disease diagnosis. In this paper, a multitarget tracking approach is proposed to assist endoscopists in identifying lesions under gastroscopy. This approach analyzes numerous preobserved gastroscopic images and constructs a gastroscopic image graph. In this way, the deformation registration between gastroscopic images is regarded as a graph search problem. During the procedure, the endoscopist marks suspicious lesions on the screen and the graph is utilized to locate and display the lesions in the appropriate frames based on the calculated registration model. Compared to traditional gastroscopic lesion surveillance methods (e.g., tattooing or probe-based optical biopsy), this approach is noninvasive and does not require additional instruments. In order to assess and quantify the performance, this approach was applied to stomach phantom data and<jats:italic>in vivo<\/jats:italic>data. The clinical experimental results demonstrated that the accuracy at angularis, antral, and stomach body was 6.3\u2009\u00b1\u20092.4\u2009mm, 7.6\u2009\u00b1\u20093.1\u2009mm, and 7.9\u2009\u00b1\u20091.6\u2009mm, respectively. The mean accuracy was 7.31\u2009mm, average targeting time was 56\u2009ms, and the<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\"><mml:mrow><mml:mi>P<\/mml:mi><\/mml:mrow><\/mml:math>value was 0.032, which makes it an attractive candidate for clinical practice. Furthermore, this approach provides a significant reference for endoscopic target tracking of other soft tissue organs.<\/jats:p>","DOI":"10.1155\/2014\/974038","type":"journal-article","created":{"date-parts":[[2014,8,24]],"date-time":"2014-08-24T21:04:21Z","timestamp":1408914261000},"page":"1-9","source":"Crossref","is-referenced-by-count":3,"title":["Gastroscopic Image Graph: Application to Noninvasive Multitarget Tracking under Gastroscopy"],"prefix":"10.1155","volume":"2014","author":[{"given":"Bin","family":"Wang","sequence":"first","affiliation":[{"name":"College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310027, China"},{"name":"Key Laboratory for Biomedical Engineering, Ministry of Education, Hangzhou, Zhejiang 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiling","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, Sir Run Run Shaw Hospital, Zhejiang 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